Craig Venter and team make a historic announcement: they’ve created the first fully functioning, reproducing cell controlled by synthetic DNA. He explains how they did it and why the achievement marks the beginning of a new era for science.

NEW YORK (GenomeWeb News) – By developing a gene expression network that incorporates information on gene interactions, co-regulation, and function, an American and Australian research team has discovered age-related gene expression differences in individuals with schizophrenia.

The researchers compared networks created from post-mortem prefrontal cortex brain region gene expression data for dozens of individuals with and without schizophrenia, creating individual networks for the case, control, and combined groups. Along with general differences in the expression of specific gene groups or “modules,” the team also identified groups of genes that were expressed differently with age, suggesting altered gene regulation — including a failure to curb the expression of some genes with age — may contribute to schizophrenia.

“[W]e hypothesize that, at least a proportion of disease pathogenesis results from a failure of normal age-related down-regulation of gene expression related to neuronal development and dopamine-related signaling,” senior author Elizabeth Thomas, a molecular biology researcher at the Scripps Research Institute, and colleagues wrote in the journal Genome Research. “These findings illuminate a novel molecular basis for schizophrenia that should facilitate diagnosis, prognosis, and therapeutic considerations.”

Schizophrenia is a complex psychiatric condition that’s thought to involve both genetic and environmental risk factors, Thomas and her co-workers explained. While past gene studies have turned up a wide range of genes with altered expression in schizophrenia, such individual gene expression changes offer a limited understanding of schizophrenia biology, the team argued.

Instead, the researchers opted for a network approach, creating modules based on co-expression data, genetic interactions, and functional information for the gene products.

“[T]he greatest molecular variation distinguishing subjects with schizophrenia from controls occurs at the level of collective changes in gene expression within functional networks and the differential effects of aging on key biological systems,” they wrote. “The power to detect these changes is dramatically improved by network co-expression analysis, which can reveal small concerted gene expression changes that may not reach individual gene-level significance due to multiple testing issues.”

The gene expression networks developed for the study brought together prefrontal cortex expression data on 13,012 genes from two post-mortem studies of individuals between 19 and 81 years old — including 47 schizophrenia patients and 54 healthy controls. For each individual, gene expression was assessed using either the Affymetrix Human Genome U133 Plus 2.0 array or the Affymetrix Human Genome U951 array.

Overall, the researchers found that the case network, which contained 2,058 genes, and the control network, which contained 2,812 genes, had overlapping connections, with similar groups of genes being co-regulated.

When they looked at the sorts of genes that were differentially expressed in the schizophrenia network, the team detected significant expression differences in five groups of genes. The affected groups housed genes involved in everything from metabolism and energy production to neuron development and differentiation to chromatin assembly and transcription.

The team also found differences in the gene expression networks when they took individuals’ age into account. For instance, the expression of three groups of genes decreased with age in the control group but not in the schizophrenia group.

One of these groups included 30 genes involved in nervous system development, neuron differentiation, and neurotransmitter receptors, and more, leading the researchers to suspect that “normal age-related decreases in genes related to [central nervous system] developmental processes, including neurite outgrowth, neuronal differentiation, and dopamine-related cellular signaling, do not occur in subjects with schizophrenia during the aging process.”

On the other hand, another three groups of genes — including genes involved in lipid metabolism, immunological disease, and gene expression — showed age-related alterations in expression in case but not control groups.

Based on these findings, those involved suggest that the pathogenic trigger for schizophrenia may not necessarily be tied solely to developmental processes occurring early in life, but may involve differences that span the individual’s lifetime. That, in turn, hints that schizophrenia treatments targeting genes that are differentially expressed and regulated may have to account for age.

This story, originally published on February 18, 2010, has been updated to include additional comments from outside sources.

In a step towards personalized cancer treatment, researchers from Johns Hopkins University have devised a sequencing strategy specifically for identifying structural rearrangements, which they said could be used to develop patient-specific “personalized biomarkers” that could be used to monitor tumor response to specific therapies.

The researchers published a proof of principle of the work last week in Science Translational Medicine and are now testing it on more patients to determine its clinical usefulness.

“We know these structural alterations are a hallmark of solid tumors; therefore identification of any alteration can be used as a diagnostic marker,” said Rebecca Leary, lead author of the study and graduate student at the Johns Hopkins Kimmel Cancer Center. “Next-gen sequencing technology allows us to rapidly identify these structural alterations, sequence the breakpoint, and then use that breakpoint for further monitoring of residual disease,” she added.

Leary and her colleagues used a sequencing strategy they dubbed “personalized analysis of rearranged ends,” or PARE, on Applied Biosystems’ SOLiD to selectively identify structural rearrangements in breast and colon cancer tumors. They sequenced two cancer and normal samples of breast cancer and colon cancer, and an additional two colon cancer samples without a normal match.

Leary said that PARE is particularly well suited for the SOLiD platform because it provides lots of paired-end reads per run, which allows them to efficiently identify rearrangements.

Stan Nelson, professor of genetics at the University of California, Los Angeles, agreed that doing the method on SOLiD was especially efficient because of the number of paired-end reads generated from the SOLiD, and he estimated that doing the same approach would be about twice as expensive on Illumina, and ten times as expensive on 454.

Leary and colleagues generated libraries with mate-paired tags 1.4 kilobases apart and used a 25 base pair mate-paired end sequencing strategy. They obtained about 198 million 25 base pair reads and 40 million mate-paired reads per sample, where the reads mapped perfectly and uniquely to the reference human genome. They achieved about 18-fold coverage.

Leary said the PARE method was designed specifically for the detection of rearrangements. “It requires much less sequencing than is needed for a complete genome assembly,” she said. “So we only sequenced enough for rearrangement detection.”

The team then looked for rearrangements. “The mate-paired tags allowed us to detect rearrangements by looking for tag pairs that map to different chromosomes, with incorrect ordering, orientation, or spacing,” said Leary. In the samples where they also sequenced the normal tissue, they compared the findings to the normal tissue to ensure that the mutations were somatically acquired.

While the team was also able to identify rearrangements in the tumor-only samples, they could not verify whether those were somatically acquired. As a result, when they tested the identified rearrangements, they were only able to confirm about 50 percent of the rearrangements in the tumor-only sample, and between 70 to 90 percent in the tumor-normal sample.

To determine whether the identified sequences would be useful biomarkers they attempted to detect them in a mixture of cancer and normal DNA. They were able to detect the biomarkers in DNA mixtures containing the equivalent of one cancer genome to 390,000 normal genomes.

They also tested the technique on an actual patient before and after surgery, and found the biomarker in the patient blood samples both before and after surgery, although in much lower concentration post surgery.

Specifically, they found that the level of mutant DNA in plasma samples was 37 percent prior to surgery but 14 percent one day after resection of the primary tumor. The amount of mutant DNA “decreased further after chemotherapy and subsequent removal of metastatic lesions from the right lobe of the liver,” the authors added, but did not reach zero, which they said was “consistent with the fact that this patient had residual metastatic lesions in the remaining left lobe of the liver.”

The study “demonstrates the possibilities of clonal markers for solid tumors, which have previously been unavailable,” said Heidi Greulich, instructor of medicine at the Dana-Farber Cancer Institute. “I think there is potential there for being able to follow the status of a tumor to treatment.”

However, she added that the approach doesn’t allow researchers to detect the location of the tumor. “It can only give overall tumor status of the patient,” she said. “It doesn’t give you spatial information the way that imaging methods would.” In the case of metastasis, knowing the location of the tumor would be particularly important.

Li Ding, research assistant professor of genetics at Washington University’s sequencing center, said the study “demonstrates the power of next-gen sequencing at low coverage for identifying structural rearrangements,” and using that method to “monitor tumor progression.” She said that the Hopkins approach — using long insert sizes so that they didn’t need as much depth of coverage — was a good way to efficiently look for rearrangements.

Ding’s group has also developed a method for detecting rearrangements, an algorithm called BreakDancer, which they developed for the Illumina platform and have used to analyze rearrangements in acute myeloid leukemia samples. She said it would be interesting to compare the two methods on the same sample, or to use them together to improve specificity.

UCLA’s Nelson added that the sequencing method itself wasn’t particularly new, but said that the researchers were able to demonstrate that they could find rearrangements without having to generate lots of data, making the method more efficient and cost effective than previously demonstrated.

He also thought that it would be useful for monitoring cancers that are often overtreated, like childhood cancers. In that case, he said the biomarkers could be used to monitor the cancer and determine when the cancer is cured. That would be useful for leukemia, because it is often unclear when treatment should be stopped. But, he added, in breast or colorectal cancer, it is rare that patients are overtreated.

The Johns Hopkins team is now testing the method on more patients and different cancer types, including 50 colorectal cancers and 50 pancreatic cancers, to see how it could be used in a clinical setting, and has filed patents on the technique. Before it could be clinically useful, though, the cost would need to come down to at least the level of conventional imaging methods, like CT scanning, which currently runs around $1,500 per scan.

The sequencing-based approach would likely be able to detect recurrent cancer before a CT scan would, but the authors noted that it currently costs around $5,000 per patient due to the level of sequencing required to identify patient-specific alterations.

“This cost is a consequence of the high physical coverage and the inefficiencies associated with stringent mapping of 25-bp sequence data to the human genome,” they wrote. “As read quality and length continue to improve, less stringent mapping criteria and lower physical coverage will permit analyses similar to those in this study but with substantially less sequencing effort.”

Leary noted that the method is “a really exciting test that could be used in a number of clinical settings.”

For example, if a patient with early-stage cancer is treated surgically, “a clinician could use this to see if the surgery was curative. Alternatively, if a patient was in the late stages of the disease, a physician could use it to monitor throughout the course of treatment to see how well the treatment is working and to assess tumor burden,” she said.

describes how structural signatures can be used to distinguish between the effects of mutation and selection in cancer genomes. Graham Bignell of the Wellcome Trust Sanger Institute and his colleagues identified 2,428 somatic homozygous deletions in 746 cancer cell lines. They then elicited “structural signatures that distinguish between homozygous deletions over recessive cancer genes and fragile sites.” The team writes that the application of these signatures to unexplained homozygous deletions revealed that many exist in regions of inherent fragility.

Also in Nature this week, a team led by researchers at the Broad Institute report that cancer cells containing amplifications surrounding MCL1 and BCL2L1 ― anti-apoptotic genes ― depend on those genes for survival. They also describe their discovery that many somatic copy-number alterations recognized in individual cancer types are present in several other cancers.

Arjun Raj of the University of Pennsylvania (formerly of MIT) and his colleagues discuss mutations in developmental networks and how they can expose variability in gene expression ― and subsequently phenotypic variation. In their study, Raj’s team examined intestinal specification in Caenorhabditis elegans, the model nematode in which cell fate is controlled by a small transcriptional network. They write that “mutations in elements of this network can have indeterminate effects: some mutant embryos fail to develop intestinal cells, whereas others produce intestinal precursors.” Raj et al. also describe their elucidation of an apparent on/off expression pattern of the master regulatory gene of intestinal differentiation in C. elegans.

Meanwhile, in Nature Biotechnology, researchers present an approach for associating genes with plant traits using a genome-scale functional network and targeted reverse genetic screening in Arabidopsis thaliana. The network, dubbed AraNet, creates predictive associations among diverse biological pathways in the model plant which outperform those derived from published literature. The paper also identifies AT1G80710 (now known as DRS1) as a drought-sensitivity regulator and AT3G05090 (LRS1) as critical in lateral root development and regulation.

Astrobiology Magazine‘s Michael Schirber

looks into Harvard Medical School’s Gary Ruvkun’s Search for Extraterrestrial Genomes project. In that project, Ruvkun and his colleagues are testing the panspermia theory, which says that biological materials can travel through space and initiate life in other locations, such as Mars or the Earth. The researchers have developed a thermocycler that uses 16S ribosomal RNA primers — which they say is likely to be conserved in Martian life as it is in Earth-bound life — to identify and amplify any Martian DNA that is closely related to Earth-based DNA. They plan to field-test the tool in Argentina this year with funding from NASA’s Astrobiology Science and Technology Instrument Development program. However, some argue that searching for Martian DNA is premature. “If there were other signs of life, more specifically biomass, I would applaud DNA analysis,” adds Norman Pace at University of Colorado, Boulder in the article. “Without even trace target biomass, talking about DNA sequences seems premature to me.”

NEW YORK (GenomeWeb News) – An international research team reported in Nature today that it has characterized five human genomes from southern Africa, identifying millions of SNPs never before found in the human population.

The American, African, and Australian researchers sequenced the full genomes of two African individuals: a member of a hunter-gatherer population in the Kalahari desert known as the Bushmen, San, or Khoisan, and a Bantu individual from South Africa — Nobel peace prize winner Archbishop Desmond Tutu. After sequencing the exomes of three other Khoisan men, the team compared all five genomes, identifying more than 1.3 million previously undetected SNPs.

During their subsequent analyses, they not only found genetic differences between southern African populations and populations from other parts of Africa and the world but also within the Khoisan population — findings that may eventually inform everything from studies of human population history and adaptations to agriculture to personalized medicine strategies in southern Africa.

“On average, there are more genetic differences between any two Bushmen in our study than between a European and an Asian,” co-lead author Stephan Schuster, a biochemistry and molecular biology researcher with Pennsylvania State University’s Center for Comparative Genomics and Bioinformatics, said in a statement.

Southern Africa is believed to be the source of modern humans and, subsequently, is home to a great deal of human genetic diversity. But despite the decades-long effort to characterize the human genome and human population genetics, most studies have lacked representatives from this region, Schuster explained during a telephone briefing with reporters this morning.

In an effort to get a better sense of the genetic variation within humans, he and his team set out to characterize the genomes of individuals from the Khoisan population — thought to be the oldest modern human population. Schuster described the project at the American Society for Human Genetics meeting last fall, though this paper marks the first publication from the sequencing effort.

Archbishop Tutu, who has ancestry from Sotho-Tswana and Nguni language groups, which represent roughly 90 percent of southern Africans, also participated in the study. Tutu was a good candidate not only because of his ancestry but also because he is known to have survived polio, tuberculosis, and prostate cancer and because he is a voice for southern Africa and indigenous populations, senior author Vanessa Hayes, a cancer genetics researcher at the University of New South Wales, told reporters.

The four Khoisan men who participated in the study all came from different communities in Namibia’s Kalahari Desert. Each was the most elder member of his community.

The team sequenced the genome of a Khoisan man named named !Gubi to 10.2 times coverage using paired-end sequencing with the Roche 454 GS FLX Titanium platform. !Gubi is believed to be around 86 years old and lives in the southern Kalahari on the Namibia-Botswana border. They also used a similar approach to sequence the genome of a second Khoisan man named G/aq’o, from a community in the northern Kalahari, to about two times coverage.

For the exome sequencing portion of the study, the team captured protein-coding sequences for each of the five individuals with the NimbleGen 2.1 M array and sequenced them by Roche 454 Titanium sequencing.

The genomic and exomic sequences were verified using a range of approaches, including genotyping and whole-genome and exome sequencing with the Illumina platform, which was used to sequence !Gubi’s genome to 23.2 times coverage and Tutu’s genome to 7.2 times coverage.

When the team compared the genomes and exomes to version 18 of the human reference genome and eight personal genomes sequenced, they found 1.3 million previously undetected SNPs, including 13,146 new SNPs that alter the amino acid sequence of 7,720 genes.

!Gubi’s genome contained more SNPs than Tutu’s, though both contained more SNPs overall — and more novel SNPs — than any other individual genome sequenced so far.

And from their population level analyses, the researchers detected as many or more genetic differences between the Khoisan and West African populations than between West African and European populations.

The team’s preliminary peek at the functional role of genes affected by new SNPs in the Khoisan population suggests that these variants tend to fall in genes involved in immune response, reproduction, and sensory perception.

“We believed that because of their extremely long lineage, their genome would be very different,” co-lead author Webb Miller, a researcher at Penn State’s Center for Comparative Genomics and Bioinformatics, told reporters. And, he said, the findings so far support that hypothesis.

This type of genetic diversity within the human genome is believed to have helped humans thrive over thousands of years, Schuster said, though he emphasized that modern human genomes from all around the world still share far more similarities than differences. “We are genetically one healthy species,” he said.

The team believes understanding human genetic diversity in southern Africa will likely be medically important, both for developing personalized medicine in this region and for identifying and understanding the roles of rare variants in human health and disease in general.

“Adding the described variants to current databases will facilitate the inclusion of southern Africans in medical researchers’ efforts, particularly when family and medical histories can be correlated with genome-wide data,” the researchers wrote.

The researchers have already started developing microarrays incorporating the newly identified southern African SNPs. For the next phase of the study, they plan to use these microarrays to genotype hundreds of individuals from southern Africa.

research out of the Scripps Translational Science Institute describes a novel method for SNP identification, “SNIP-Seq.” SNIP-Seq utilizes population sequence data to detect SNPs and assign genotypes to individuals. The team used data from a region on chromosome 9p21 of the human genome (sequenced in 48 individuals, with five sequenced in duplicate) and found that many of the novel SNPs identified by SNIP-Seq were validated by pooled sequencing data; they were also confirmed by Sanger sequencing. “Collectively, these results suggest that analysis of population sequencing data is a powerful approach for the accurate detection of SNPs and the assignment of genotypes to individual samples,” the team writes.

Also published in advance online this week, Wilfried Haerty and G. Brian Golding of McMaster University, Ontario, describe their discovery of genome-wide evidence for selection acting on single amino acid repeats. Haerty and Golding tested the effect of splicing on the structure of homopolymer sequences. The team discerned a “relationship between alternative splicing and homopolymer sequences with alternatively spliced genes being enriched in number and length of homopolymer sequences.” They also found lower codon density and longer homocodons, which they say suggests a balance connected with the pressures imposed by selection.

This week in Genome Research, researchers at Harvard and MIT propose an improved method for identifying gene interactions using high-dimensional single-cell morphological data from genetic screens, applied in a systematic computational model to RhoGAP/GTPase regulation in Drosophila melanogaster. The team writes that while their model appears to create only mediocre predictions, it represents a vast improvement from alternative methods. “This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations,” they write.

In a methods paper, Andrew Young of the National Human Genome Research Institute and his colleagues describe a novel strategy for de novo genomic assemblies using short sequence reads and reduced representation libraries. Young et al. developed a method to partition the genome prior to assembly by using two independent restriction enzymes to create overlapping fragment libraries ― each containing a manageable subset of the genome. “Together, these libraries allow us to reassemble the entire genome without the need of a reference sequence,” the team writes. In a proof-of-concept study, the team applied their method in assembling the Drosophila genome, and when compared with the reference genome, they deemed their version significantly comparable.

FROM adhesives that mimic the feet of geckos to swimsuits modelled on shark skin, biologically inspired design has taken off in recent times. Copying nature’s ideas allows people to harness the power of evolution to come up with clever products. Now a group of researchers has taken this idea a step further by using an entire living organism—a slime mould—to solve a complex problem. In this case, the challenge was to design an efficient rail network for the city of Tokyo and its outlying towns.

Slime moulds are unusual critters—neither animal, nor plant nor fungus. If they resemble anything, it is a colonial amoeba. Physarum polycephalum, the species in question, consists of a membrane-bound bag of protoplasm and, unusually, multiple nuclei. It can be found migrating across the floor of dark, damp, northern-temperate woodlands in search of food such as bacteria. It can grow into networks with a diameter of 25cm.

When P. polycephalum is foraging, it puts out protrusions of protoplasm, creates nodes and branches, and grows in the form of an interconnected network of tubes. As it explores the forest floor, it must constantly trade off the cost, efficiency and resilience of its expanding network.

Since the purpose of this activity is to link food sources together and to transport nutrients around the creature, Atsushi Tero at Hokkaido University in Japan and his colleagues wondered if slime-mould transport networks bore any resemblance to human ones. As they report in Science, they built a template with 36 oat flakes (a favoured food source) placed to represent the locations of cities in the region around Tokyo. They put P. polycephalum on Tokyo itself, and watched it go.

They found that many of the links the slime mould made bore a striking resemblance to Tokyo’s existing rail network. For P. polycephalum had not simply created the shortest possible network that could connect all the cities, but had also included redundant connections that allow the creature (and the real rail network) to have resilience to the accidental breakage of any part of it. P. polycephalum’s network, in other words, had similar costs, efficiencies and resiliencies to the human version.

How the creature does this is unknown, but Mark Fricker of Oxford University, who is one of Dr Tero’s colleagues, speculates that the forces generated by protoplasm pulsating back-and-forth through the multinuclear cell are interpreted and used to determine which routes to reinforce, and which connections to trim.

Tokyo’s is not the first transport network to be modelled in this way. A study published in December by Andrew Adamatzky and Jeff Jones of the University of the West of England used oat flakes to represent Britain’s principal cities. Slime moulds modelled the motorway network of the island quite accurately, with the exception of the M6/M74 into Scotland (the creatures chose to go through Newcastle rather than past Carlisle).

Of course, neither Dr Tero nor Dr Adamatzky is suggesting that rail and road networks should be designed by slime moulds. What they are proposing is that good and complex solutions can emerge from simple rules, and that this principle might be applied elsewhere. The next thing is to discover and use these rules to enable other networks to self-organise in an “intelligent” fashion without human intervention—for example, to link up a swarm of robots exploring a dangerous environment, so that they can talk to each other and relay information back to base. The denizens of Carlisle, meanwhile, may wonder what objection slime moulds have towards their fine city.

January 20th, 2010 Brian Mossop Leave a comment Go to comments
One morning, a little over a year ago, I woke up with a very sore, and slightly swollen elbow. I remembered that I had cut my arm on a neighborhood bar table while watching a football game with some friends a few days prior, and I wondered if the cut was infected. I made an appointment with my primary care physician, who quickly diagnosed me with bursitis, an inflammation of the fluid-filled sac that pads the elbow. Since I had broken skin, the doctor wisely prescribed clindamycin, an antibiotic, to treat any tissue infection that may have seeped in.

As the hours crept by, the pain in my elbow worsened, until I woke up in the middle of the night with extreme arm pain. I immediately checked the elbow that had been swollen the previous day. The swelling had doubled in size, and the skin was an angry-red color. The following morning, I was back in the clinic, and my doctor started to suspect that this was no ordinary infection on my elbow, and may in fact be a drug-resistant staph infection. Gulp. Nonetheless, he felt confident that the clindamycin should clear it up.

Under the doctor’s orders, I spent the next day meticulously tracing the swollen area on my elbow with a Sharpie marker, carefully noting how much it spread. By the end of the day, my entire forearm was puffy and discolored, and my doctor said it was time for me to be admitted to the hospital. I spent 3 days there, getting intravenous treatments of vein-burning, gastrointestinal-rearranging Vancomycin pumped into my system. Not fun.

Afterward, I talked to a number of physician friends about my experience. They said my doctor’s treatment plan was textbook. He had done everything right. When docs suspect drug-resistant staph, the first line of defense is typically a hearty dose of clindamycin. The problem in my case was that the staph I contracted was actually resistant to clindamycin. That explains why the infection continued to spread even though I was taking the antibiotics.

Since this little microbial foray, I’ve had a growing interest in infectious disease. Specifically, I like seeing smart, new ways to keep tabs on how bacterium move from place to place. I wonder, if my doctor had known that clindamycin-resistant staph was infiltrating San Francisco, would I have initially received a different antibiotic? In my opinion, this was a clear case where having more data would have aided the diagnosis, and hastened a healthy outcome.

As Thomas pointed out at The Huffington Post, the true promise of personalized medicine is more about data than specialty drugs. Data can be our personal metrics, such as blood pressure, glucose levels, or cholesterol values. But keeping medical data to ourselves would be somewhat shortsighted. The internet has taught us the power of sharing data. We share our photos on Flickr. We share our status messages on Facebook. We share links on Twitter. Likewise, we can share our health and medical data, enabling pooled statistics from large populations. In the case of infectious disease, the best preventive strategy is to know exactly what strains you’re up against, and how the microbes are moving into different geographic regions over time.

Researchers recently confirmed the power of sharing microbial data in a new report, published this month in PLoS Medicine. Roughly 25% TK of us walk around with staph on our skin, yet not all of us get sick. That’s because there’s relatively few strains that cause serious symptoms. These so-called virulent strains are the ones docs want to track.

Following both methycilin-resistant (MRSA) and methycilin-susceptible (MSSA) staph strains through Europe, the authors coordinated the participation of 450 hospitals in 26 European countries, a logistic feat in its own right. When a case of staphylococcus aureus was found, the bacterium was genotyped (i.e. its DNA was analyzed to identify which strain it came from), and its location recorded. After collecting all the data, researchers could see how a particular strain of staph localized in different geographic regions. For instance, did the virulent strains stay in one hospital, or had they spread throughout the community?

The authors found that most virulent MRSA strains were contained in a health care clinic, meaning that drug-resistant staph was simply hopping from person-to-person within the hospital walls. Occasionally, that MRSA strain would show up at a different, nearby hospital, and rapidly spread in admitted patients. This implies that the carriers of the virulent MRSA strains are patients who are repeatedly admitted to different regional hospitals.

I’ll leave you with a final thought: tracking microbes isn’t just a task for researchers. In fact, DIYBio types should check out a cool new project called BioWeatherMap, which asks volunteers to swab commonly used public surfaces, such as door knobs or crosswalk buttons, to track pending microbial storm fronts.